Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

Journal: Pancreas
PMID: 38019604

Abstract

OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC).

Authors

  • Taishu Kanda
  • Taiichi Wakiya
    Department of Gastroenterological Surgery, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki City, Aomori, 036-8562, Japan. wakiya1979@hirosaki-u.ac.jp.
  • Keinosuke Ishido
    Department of Gastroenterological Surgery, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki City, Aomori, 036-8562, Japan.
  • Norihisa Kimura
    Department of Gastroenterological Surgery, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki City, Aomori, 036-8562, Japan.
  • Hayato Nagase
    Department of Gastroenterological Surgery, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki City, Aomori, 036-8562, Japan.
  • Eri Yoshida
  • Junichi Nakagawa
    Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, N15 W7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Masashi Matsuzaka
    Department of Medical Informatics, Hirosaki University Hospital, Hirosaki City, Aomori, 036-8562, Japan.
  • Takenori Niioka
    Departments of Pharmacy.
  • Yoshihiro Sasaki
    Department of Medical Informatics, Hirosaki University Hospital, 53 Hon-cho, Hirosaki, 036-8563, Japan. Electronic address: gahiro@hirosaki-u.ac.jp.
  • Kenichi Hakamada

Keywords

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